Nikunj C. Oza - Concepedia

Author

Nikunj C. Oza

Ames Research Center ORCID

Also Known As

Kittler, Josef, N. Oza, N.C. Oza, NIKUNJ OZA, Neel Oza, Nikunj C Oza, Nikunj C. Oza, Nikunj Oza, Oza, N., Oza, Nikunj

122

Publications

3.5K

Citations

H-Index

115

Concepts

All Affiliations

Ames Research Center University of Illinois Urbana-Champaign University of Minnesota Universities Space Research Association University of California, Berkeley

About

Nikunj C. Oza is an author at Ames Research Center specializing in engineering, data science, and knowledge discovery.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Engineering	23	32	2.6K
2	Management	7	7	511
3	Business	2	2	98
4	Education	2	2	28
5	Arts	1	1	26

Nikunj C. Oza

Publications

Citations

H-Index

Page 1

	Year	Citations
Online Bagging and Boosting Nikunj C. Oza Batch ModeMachine LearningEngineeringOnline ProblemData Science	2006	567
Online Bagging and Boosting Nikunj C. Oza, Stuart Russell NASA Technical Reports Server (NASA)	2001	333
Classifier ensembles: Select real-world applications Nikunj C. Oza, Kagan Tumer Information Fusion EngineeringMachine LearningData MiningPattern RecognitionClassifier Ensembles	2007	311
Experimental comparisons of online and batch versions of bagging and boosting Nikunj C. Oza, Stuart Russell Artificial IntelligenceEngineeringMachine LearningMachine Learning ToolOnline Versions	2001	247
Online Ensemble Learning Nikunj C. Oza Artificial IntelligenceIncremental LearningEngineeringMachine LearningMining Methods	2000	187
Multiple kernel learning for heterogeneous anomaly detection Santanu Das, Bryan Matthews, Ashok N. Srivastava, Anomaly DetectionMachine LearningEngineeringIntelligent SystemsData Science	2010	182
Classification and Adaptive Novel Class Detection of Feature-Evolving Data Streams Mohammad Mehedy Masud, Qing Chen, Latifur Khan, IEEE Transactions on Knowledge and Data Engineering Incremental LearningEngineeringMachine LearningStreaming AlgorithmStreaming Data	2012	120
Facing the reality of data stream classification: coping with scarcity of labeled data Mohammad Mehedy Masud, Clay Woolam, Jing Gao, Knowledge and Information Systems Data StreamEngineeringMachine LearningData ScienceData Mining	2011	119
Outlook for Exploiting Artificial Intelligence in the Earth and Environmental Sciences Sid‐Ahmed Boukabara, Vladimir M. Krasnopolsky, Stephen G. Penny, Bulletin of the American Meteorological Society Artificial IntelligenceEnvironmental MonitoringEngineeringEnvironmental Impact AssessmentWeather Forecasting	2020	88
Input decimated ensembles Kagan Tumer, Nikunj C. Oza Pattern Analysis and Applications EngineeringMachine LearningData ScienceData MiningMultiple Classifier System	2003	77

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